Title（题目）
On Multiple Testing and the Monotone Likelihood Ratio Condition
Speaker（报告人）
Hongyuan Cao, PhD
Assistant Professor in Department of Health Studies, the University of Chicago
Time（时间）
2011年4月20日（周三）上午10：00-11：00
Place（地点）
中国人民大学明主1016
Abst
ract（摘要）
High-throughput screening has become an important mainstay for contemporary biomedical research. A standard approach is to get p-values and adjust for multiple comparison in a manner that controls false discovery rate (FDR). The concavity of p-value distribution under the alternative has been a standard condition for developing many FDR procedures: Storey (2003), Genovese and Wasserman (2004), Kosorok and Ma (2007). A more general concept is the monotone likelihood ratio condition (MLRC) introduced in Sun and Cai (2007). We show in this paper that the concavity assumption can be violated for (i) a simple heteroscedastic normal mixture model and (ii) dependent tests. Some interesting implications, including different testing procedures (step-up vs step-down), the choice of test statistic and the power de_nition in multiple testing are discussed. This is joint work with Wenguang Sun and Michael R. Kosorok.
